lme4: Mixed-effects models in R.

Recent/release notes

• See the NEWS file

Where to get help

• [email protected] for questions about lme4 usage and more general mixed model questions; please read the info page, and subscribe, before posting ... (note that the mailing list does not support images or large/non-text attachments)
• https://github.com/lme4/lme4/issues for bug, infelicity, and wishlist reporting
• The lme4 tag on StackOverflow for programming-related or the lme4-nlme tag on CrossValidated for statistics-related questions
• maintainer e-mail only for urgent/private communications

Please do not cross-post, i.e. ask the same question in more than one forum, unless it's suggested that you have posted in the wrong place, or unless you receive total silence in one forum. In the latter case it may be better to send a reminder/"bump" message to the original forum; in any case you should mention in your new message where/when you've previously asked the question.

Support

If you choose to support lme4 development financially, you can contribute to a fund at McMaster University (home institution of one of the developers) here. The form will say that you are donating to the "Global Coding Fund"; this fund is available for use by the developers, under McMaster's research spending rules. We plan to use the funds, as available, to pay students to do maintenance and development work. There is no way to earmark funds or set up a bounty to direct funding toward particular features, but you can e-mail the maintainers and suggest priorities for your donation.

Features

• Efficient for large data sets, using algorithms from the Eigen linear algebra package via the RcppEigen interface layer.
• Allows arbitrarily many nested and crossed random effects.
• Fits generalized linear mixed models (GLMMs) and nonlinear mixed models (NLMMs) via Laplace approximation or adaptive Gauss-Hermite quadrature; GLMMs allow user-defined families and link functions.
• Incorporates likelihood profiling and parametric bootstrapping.

Installation

On current R (>= 3.6.0)

(note: we haven't tested installation of lme4 on now-ancient versions of R recently. There may be recursive package dependencies that impede installation on old versions; if you experience such problems please post an issue and we'll do our best to resolve the problem)

• From CRAN (stable release 1.+)
• Development version from Github:

library("devtools"); install_github("lme4/lme4",dependencies=TRUE)

(This requires devtools >= 1.6.1, and installs the "master" (development) branch.) This approach builds the package from source, i.e. make and compilers must be installed on your system -- see the R FAQ for your operating system; you may also need to install dependencies manually. Specify build_vignettes=FALSE if you have trouble because your system is missing some of the LaTeX/texi2dvi tools.

• Development binaries from r-universe:

install.packages('lme4', repos = c('https://lme4.r-universe.dev', getOption("repos")[["CRAN"]]))

Development notes

lme4 is developed in a mixture of

• traditional R package building tools, as documented in Writing R Extensions
  • NEWS in inst/NEWS.Rd (not a top-level NEWS.md file)
  • documentation as .Rd files (not roxygen2, although some functions have internal roxygen-style documentation [not used])
  • 'classic' tests in the tests/ directory
  • some Sweave (knitr)/Rnw-format vignette, especially vignettes/lmer.Rnw
• 'tidyverse'-style tools, as documented in R Packages (Wickham and Bryan)
  • testthat tests, in tests/testthat
  • pkgdown web site (via pkgdown.extras, extensions to allow PDF vignettes); trigger manual builds here
• GitHub
  • primary development repository
  • issues
  • testing on GitHub actions (activated by specifying "[run ci]" at the end of a commit message)
  • pull requests are welcome, but please open a discussion as an issue first